library(igraph)


Attaching package: ‘igraph’

The following objects are masked from ‘package:stats’:

    decompose, spectrum

The following object is masked from ‘package:base’:

    union
result_food_uft_DEL_k <- result_food_uft_DEL_k[,3:20]
head(result_food_uft_DEL_k)
EDL_Embedding = read.csv('/Users/xbasra/Documents/Data/Clustering_Food_Alergies/CsvData/EDL_Embedding.csv')
head(EDL_Embedding)
Em_corr <- cor(t(EDL_Embedding))
Em_corr[Em_corr < 0.9995] <- 0
network <- graph_from_adjacency_matrix( Em_corr, weighted=T, mode="undirected", diag=F)
plot(network)
set.seed(10)
#tsne_converted_food_DEL <- Rtsne(X = EDL_Embedding ,perplexity= 200, is_distance = FALSE, check_duplicates = FALSE)
tsne_converted_food_DEL <- Rtsne(X = EDL_Embedding ,perplexity= 150, is_distance = FALSE, check_duplicates = FALSE)
tsne_converted_food_DEL <- tsne_converted_food_DEL$Y %>%
  data.frame() %>%
  setNames(c("X", "Y"))
tsne_converted_food_DEL$cl <- factor(result_food_uft_DEL_k$cluster)
ggplot(tsne_converted_food_DEL, aes(x=X, y=Y, color=cl)) + geom_point()

#ggplot(aes(x = X, y = Y), data = tsne_converted_food_DEL)  + geom_point()
library(plotly)
#packageVersion('plotly')
tsne_converted_food_DEL_3d <- Rtsne(X = EDL_Embedding ,perplexity= 150, dims = 3, is_distance = FALSE, check_duplicates = FALSE)
tsne_converted_food_DEL_3d <- tsne_converted_food_DEL_3d$Y %>%
  data.frame() %>%
  setNames(c("X", "Y", "Z"))
tsne_converted_food_DEL_3d$cl <- factor(result_food_uft_DEL_k$cluster)
p <- plot_ly(tsne_converted_food_DEL_3d, x = ~X, y = ~Y, z = ~Z, color = ~cl, colors = c('#BF382A', '#0C4B8E')) %>%
  add_markers() %>%
  layout(scene = list(xaxis = list(title = 'Dim1'),
                     yaxis = list(title = 'Dim2'),
                     zaxis = list(title = 'Dim3')))
p
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